A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem

Paul Bergey (), Cliff Ragsdale and Mangesh Hoskote

Annals of Operations Research, 2003, vol. 121, issue 1, 33-55

Abstract: Due to a variety of political, economic, and technological factors, many national electricity industries around the globe are transforming from non-competitive monopolies with centralized systems to decentralized operations with competitive business units. A key challenge faced by energy restructuring specialists at the World Bank is trying to simultaneously optimize the various criteria one can use to judge the fairness and commercial viability of a particular power districting plan. This research introduces and tests a new algorithm for solving the electrical power districting problem in the context of the Republic of Ghana and using a random test problem generator. We show that our mimetic algorithm, the Simulated Annealing Genetic Algorithm, outperforms a well-known Parallel Simulated Annealing heuristic on this new and interesting problem manifested by the deregulation of electricity markets. Copyright Kluwer Academic Publishers 2003

Keywords: electricity deregulation; genetic algorithms; simulated annealing; multi-criteria decision making (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1023/A:1023347000978

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